Okendo

Okendo offers a customer marketing platform designed to enhance growth opportunities and foster customer loyalty by leveraging social proof, facilitating word-of-mouth marketing, and driving conversions for brands.

Professional Services

Industrials

11-50 (30)

Founded 2016

$31M raised

8 open positions

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Analytics Engineer

2 hours, 35 minutes ago

Australia

Full-time

Mid Level

Analytics Engineer

Data Science and Analytics

Apache Airflow AWS Dagster dbt Feature Engineering Looker Machine Learning Pandas Power BI Python SQL Tableau

Apply Now

Okendo

Professional Services

11-50

Founded 2016

$31M raised

View All Jobs 8

Description

Build and maintain feature marts for machine learning pipelines in partnership with Data Science.
Design and implement DBT-based data transformations and maintain reliable, well-documented pipelines from multiple source systems.
Create and manage datasets that support self-service analytics for Product, GTM, and Customer Success teams.
Develop dashboards and reports in QuickSight for stakeholders and translate business questions into actionable insights.
Perform ad-hoc analyses to support product and business decisions.
Ensure data quality and reliability through testing, documentation, and monitoring.
Collaborate with cross-functional teams to understand data needs and deliver scalable solutions.
Own the data layer and help unblock ML models by providing production-ready feature sets.
Identify and drive data initiatives that improve how the business uses data.

Requirements

3-5 years of experience in analytics engineering, data engineering, or a similar role.
Ability to work autonomously in a fast-paced, evolving environment.
Strong communication skills with the ability to translate technical concepts for non-technical stakeholders.
Strong SQL skills, including complex querying, query optimization, and working with large datasets.
Experience with DBT or similar transformation tools and data modeling best practices.
Data visualization experience; QuickSight preferred, with Tableau, Looker, or Power BI also valued.
Experience with Python for data manipulation, including pandas, basic scripting, and data wrangling.
Hands-on experience with AWS data services such as Redshift, Athena, and S3, or similar cloud data platforms.
Experience in e-commerce or SaaS environments is preferred.
Familiarity with ML feature engineering and productionization is preferred.
Experience with data orchestration tools such as Airflow or Dagster is preferred.
Understanding of data governance and documentation practices is preferred.
Experience working in high-growth or startup environments is preferred.

Benefits

Remote work in Australia.
12 weeks of paid family leave at 100%.
Office stipend for setup.
Opportunities for training and development.
Data-backed and competitive compensation strategy.
4 weeks of annual leave.
11 paid public holidays.
Sick leave, carer’s leave, compassionate leave, and bereavement leave.

Interested in this position?

Apply directly on the company website

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